An Improved Grid-Based Approximation Algorithm for POMDPs

Although a partially observable Markov decision process (POMDP) provides an appealing model for problems of planning under uncertainty, exact algorithms for POMDPs are intractable. This motivates work on approximation algorithms, and grid-based approximation is a widely-used approach. We describe a novel approach to grid-based approximation that uses a variable-resolution regular grid, and show that it outperforms previous grid-based approaches to approximation.

• Type: Conference
• Year: 2001
• Where: IJCAI
• Authors: Rong Zhou, Eric A. Hansen
• Keywords: Approximation Algorithms, Grid-based Approximation, IJCAI 2001, IJCAI 2007, Partially Observable Markov Decision Process